Signal dispersion, such as echoes, ghosts, multipath and intersymbol interference, is an ever-present reality in communications systems. The severity of this problem varies with the system application and, at times, can render a system completely inoperative. For example, signal ghosts or echoes at levels which are merely objectional to the viewer of a conventional television signal can render a high-definition television (HDTV) signal unintelligible. Accordingly, the cancellation or compensation for such dispersion cannot be ignored.
In order to cancel or compensate for signal dispersion, certain information about the transmission channel is required. Such information is referred to as a characterization of the transmission channel. Several techniques to characterize a dispersive transmission channel are known. These techniques basically utilize circuitry which processes samples of the received signal to generate a waveform from which characteristics or the impulse response of the dispersive transmission channel can be readily determined.
Present techniques to cancel signal dispersion further include the use of filters or equalizers whose tap-weight coefficients are adjusted to optimally cancel signal dispersion. While a variety of filters are known, two commonly known filters are finite impulse response (FIR) and infinite impulse response (IIR) filters. By definition, an FIR and an IIR filter are, respectively, filters whose time-domain responses are respectively finite and infinite. Such filters are also referred to as having a reciprocal relationship when they are arranged so that the frequency response of one is the reciprocal of the other.
A variety of techniques for adjusting FIR and IIR filters are also known. These include the least-mean-squared (LMS) algorithm, and the combination of fast Fourier transform (FFT) and inverse fast Fourier transform (IFFT) algorithms. While these techniques provide satisfactory results, they are complex and require arithmetic precision that render them not particularly suitable for implementation in large-scale integrated (LSI) circuits. Moreover, the cost, size, and power consumption requirements of such an implementation are impractical in certain system applications, such as television transmission. Accordingly, it would be desirable if a technique for adjusting signal dispersion apparatus could be developed which could provide the requisite precision and yet be readily implementable in an integrated circuit.